Computer Implemented Methods and Systems for Project Management

1. A computer implemented method comprising: displaying, by a user computer in a user interface of the user computer, a scheduling interface including a first work item user interface element corresponding to a first work item stored by a data storage system of a project management server application hosted by a server, the first work item user interface element having an original length and depicting: a scheduled start date of the first work item at a first end of the original length of the first work item user interface element; an original scheduled end date for the first work item at a second end of the original length of the first work item user interface element, separated from the scheduled start date of the first work item by the original length; a scheduled start date adjustment control proximate to the first end of the first work item user interface element; and an end date adjustment control proximate to the second end of the first work item user interface element, wherein in response to an input dragging the end date adjustment control by at least a minimum amount; the original length of the first work item user interface element is changed to a new length different from the old length by the at least the minimum amount; and the user computer transmits a signal to a forecasting server in communication with the project management server application and the user computer, the signal comprising a new scheduled end date for the first work item, the new scheduled end date determined based on the new length of the first work item user interface element; receiving, from the forecasting server after the input is received, forecast data generated in response to the signal and in respect of the first work item and the new scheduled end date; determining, based on the forecast data, a forecast range based at least in part on a start date of a second work item stored by the data storage system, the second work item having a dependency relationship with the first work item, the dependency relationship stored by the data storage system; and displaying, by the user computer, a forecast user interface element on the scheduling interface and at least partially intersecting an end of a second work item user interface element corresponding to the second work item, the forecast user interface element having a length corresponding to the forecast range.

2. The computer implemented method of claim 1 , wherein: the forecast range is a first forecast range; the forecast user interface element is a first forecast user interface element; and the method further comprises: determining, based on the forecast data, a second forecast range in respect of the first work item; and displaying a second forecast user interface element overlaying at least in part the first work item interface element, corresponding to the first work item, and based on the second forecast range.

3. The computer implemented method of claim 2 , wherein: the first forecast range is a forecast start date range; and the second forecast range is a forecast end date range.

4. The computer implemented method of claim 2 , wherein: the first forecast range is a first forecast start date range and is associated with a first confidence interval; and the second forecast range is a second forecast start date range and is associated with a second confidence interval.

5. The computer implemented method of claim 1 , wherein: in response to determining that the forecast data forecasts the dependency relationship between the first and second work items to be broken, displaying a dependency path between the first and second work items indicating that the dependency relationship between the first and second work items is forecast to be broken.

6. The computer implemented method of claim 1 , wherein generation of the forecast data comprises: calculating a set of actual work item durations based on historical work item data, the set of actual work item durations including one or more actual work item durations, each actual work item duration being an actual duration of a completed work item; calculating an average work item duration based on the one or more actual work item durations in the set of actual work item durations; and returning the average work item duration as the forecast data.

7. The computer implemented method of claim 6 , wherein the actual duration of the completed work item is calculated to be a duration between an actual start date at which the completed work item transitioned to an in progress state and an actual end date at which the completed work item last transitioned to a done state.

8. The computer implemented method of claim 1 , wherein generation of the forecast data comprises: calculating a set of actual work item durations based on historical work item data, the set of actual work item durations including one or more actual work item durations, each actual work item duration being an actual duration of a completed work item; calculating a defined number of average work item durations based on the one or more actual work item durations in the set of actual work item durations; and returning the defined number of average work item durations as the forecast data.

9. The computer implemented method of claim 8 , wherein calculating a given average work item duration comprises: selecting a defined number of actual work item durations from the set of actual work item durations; and calculating an average duration of the selected defined number of actual work item durations.

10. The computer implemented method of claim 1 , wherein generation of the forecast data comprises: calculating a set of actual work item durations based on historical work item data, the set of actual work item durations including one or more actual work item durations, each actual work item duration being an actual duration of a completed work item; calculating a defined number of average work item durations based on the one or more actual work item durations in the set of actual work item durations; and using the defined number of average work item durations to generate a work item duration probability distribution; selecting one or more forecast durations according to one or more corresponding confidence intervals; and returning the one or more selected forecast durations as the forecast data.

11. A computer processing system comprising: a processing unit; a communication interface; an input device; a display device; and a non-transient computer-readable storage medium storing sequences of instructions, which when executed by the processing unit, cause the processing unit to: display on the display device a scheduling interface including a first work item user interface element representing a first work item selected from a set of work items associated with a project stored in a data storage system of a project management server application hosted by a server in communication with the processing unit via the communication interface, the first work item user interface element comprising: an original length; a first end corresponding to a scheduled start date of the first work item; and a second end corresponding to a scheduled end date for the first work item; wherein in response to an input received to the second end of the first work item user interface element via the input device: the second end is configured to change position relative to the first end by at least a minimum amount; and the scheduling interface is configured to send a work item update to the data storage system, the work item update comprising a new end date for the first work item that is based at least in part on the change in position of the second end; after the work item update is received at the data storage system, receive forecast data generated in respect of the new end date of the first work item; determine, based on the forecast data, a forecast range in respect of a second work item dependent upon completion of the first work item; and display a forecast user interface element on the scheduling interface and at least partially overlaying a second work item user interface element associated with the second work item, the forecast user interface element corresponding to a start date of the second work item, the forecast user interface element having an appearance based on the forecast range.

12. The computer processing system of claim 11 , wherein execution of the sequences of instructions further causes the processing unit to: determine, based on the forecast data, a second forecast range in respect of the second work item; and display a second forecast user interface element corresponding to the second work item and based on the second forecast range.

13. The computer processing system of claim 12 , wherein: a first forecast range is a forecast start date range; and the second forecast range is a forecast end date range.

14. The computer processing system of claim 12 , wherein: a first forecast range is a first forecast start date range and is associated with a first confidence interval; and the second forecast range is a second forecast start date range and is associated with a second confidence interval.

15. The computer processing system of claim 11 , wherein: execution of the sequences of instructions further causes the processing unit to: display the second work item user interface element on the scheduling interface, the second work item user interface element corresponding to the second work item, the first and second work items being in a dependency relationship with each other; determine that the forecast data forecasts the dependency relationship between the first and second work items to be broken and, in response, display a dependency path between the first and second work item user interface elements indicating that the dependency relationship between the first and second work items is forecast to be broken.

16. The computer processing system of claim 11 , wherein generation of the forecast data comprises: calculating a set of actual work item durations based on historical work item data, the set of actual work item durations including one or more actual work item durations, each actual work item duration being an actual duration of a completed work item; calculating an average work item duration based on the one or more actual work item durations in the set of actual work item durations; and returning the average work item duration as the forecast data.

17. The computer processing system of claim 16 , wherein the actual duration of the completed work item is calculated to be the actual duration between an actual start date at which the completed work item transitioned to an in progress state and an actual end date at which the completed work item last transitioned to a done state.

18. The computer processing system of claim 11 , wherein generation of the forecast data comprises: calculating a set of actual work item durations based on historical work item data, the set of actual work item durations including one or more actual work item durations, each actual work item duration being an actual duration of a completed work item; calculating a defined number of average work item durations based on the one or more actual work item durations in the set of actual work item durations; and returning the defined number of average work item durations as the forecast data.

19. The computer processing system of claim 18 , wherein calculating a given average work item duration comprises: selecting a defined number of actual work item durations from the set of actual work item durations; and calculating an average duration of the selected defined number of actual work item durations.

20. The computer processing system of claim 11 , wherein generation of the forecast data comprises: calculating a set of actual work item durations based on historical work item data, the set of actual work item durations including one or more actual work item durations, each actual work item duration being an actual duration of a completed work item; calculating a defined number of average work item durations based on the one or more actual work item durations in the set of actual work item durations; and using the defined number of average work item durations to generate a work item duration probability distribution; selecting one or more forecast durations according to one or more corresponding confidence intervals; and returning the one or more selected forecast durations as the forecast data.